Reimagining Application User Interface (UI) Design using Deep Learning Methods: Challenges and Opportunities

In this paper, we present a review of the recent work in deep learning methods for user interface design. The survey encompasses well known deep learning techniques (deep neural networks, convolutional neural networks, recurrent neural networks, autoencoders, and generative adversarial networks) and...

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Bibliographic Details
Published in:arXiv.org 2023-03
Main Authors: Malik, Subtain, Saeed, Muhammad Tariq, Marya Jabeen Zia, Rasool, Shahzad, Liaquat Ali Khan, Mian Ilyas Ahmed
Format: Article
Language:English
Subjects:
Artificial neural networks
Deep learning
Generative adversarial networks
Industrial development
Machine learning
Potential fields
Recurrent neural networks
Software development
Online Access:Get full text
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Summary:In this paper, we present a review of the recent work in deep learning methods for user interface design. The survey encompasses well known deep learning techniques (deep neural networks, convolutional neural networks, recurrent neural networks, autoencoders, and generative adversarial networks) and datasets widely used to design user interface applications. We highlight important problems and emerging research frontiers in this field. We believe that the use of deep learning for user interface design automation tasks could be one of the high potential fields for the advancement of the software development industry.
ISSN:2331-8422